Course Description

This anomaly detection course using AI teaches you how to identify unusual patterns or outliers in large datasets, which can be crucial for fraud detection, predictive maintenance, medical diagnosis, and other applications. You'll learn about various AI techniques like machine learning and deep learning, and how to apply them to real-world problems. This knowledge is highly valuable in today's data-driven world and can significantly boost your career prospects in fields like data science, cybersecurity, and finance.

This intensive 5-day program will provide participants with a comprehensive understanding of anomaly detection techniques using Artificial Intelligence (AI). We will explore the fundamental concepts, explore various AI algorithms, and delve into real-world applications across different domains.

Course Objectives

Upon the successful completion of this course, each participant will be able to:

  • Understand the core concepts of anomaly detection and its significance
  • Explore various types of anomalies and their characteristics
  • Implement and evaluate different AI algorithms for anomaly detection
  • Apply anomaly detection techniques to real-world datasets and scenarios
  • Develop and deploy anomaly detection solutions using appropriate tools and technologies

Who Should Attend?

This course is designed for Data scientists, machine learning engineers, researchers, and professionals interested in applying AI for anomaly detection in their respective fields.

Course Agenda

DAY 1

Registration, Welcome & Introduction

Pre-Test

Introduction to Anomaly Detection

  • What is anomaly detection? (Definitions and scope)

               √   Types of anomalies: point, contextual, collective

               √   Real-world relevance and impact (e.g., fraud, intrusion, system failures)

               √   Traditional vs AI-driven approaches

DAY 2

Machine Learning Techniques for Anomaly Detection

  • Supervised vs Unsupervised approaches
  • Core algorithms:

                √   Clustering (k-Means, DBSCAN)

                √   Isolation Forests

                √   One-Class SVM

DAY 3

Deep Learning for Anomaly Detection

  • Autoencoders: how compression reveals anomalies
  • Recurrent Neural Networks (LSTM) for sequential data
  • Comparison with traditional methods
  • Tools & Libraries (overview only)

DAY 4

Applications Across Industries

  • Finance: Credit card fraud, AML
  • Cybersecurity: Intrusion detection, behavioral monitoring
  • Healthcare: Diagnostic alerts, monitoring equipment
  • Manufacturing: Quality control, predictive maintenance

DAY 5

Ethics, Interpretability, and Future Outlook

  • Importance of explainability: SHAP, LIME (conceptual only)
  • Risks: False positives, automation bias, data privacy
  • Governance and compliance
  • Trends: Self-supervised learning, federated learning, AI Ops

Post-Test

End of the Course

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.